Use of decision trees in colour feature selection: application to object recognition in outdoor scenes
A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2000 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/2299 |
| Acceso en línea: | http://hdl.handle.net/10256/2299 |
| Access Level: | acceso abierto |
| Palabra clave: | Algorismes computacionals Discriminació visual Imatges -- Processament Reconeixement òptic de formes Visió per ordinador Computer algorithms Computer vision Image processing Optical pattern recognition Visual discrimination |
| Sumario: | A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported |
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